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istock

Why Your Family Name Did Not Come From a Mistake at Ellis Island

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istock

When my great-grandfather Yuroslav Hieronymous O’Kagan vaan de Schulevitzberg arrived at Ellis Island in 1909 he didn’t speak much English. He was 17 and hoping to make his fortune quickly and bring the rest of his family over from the old country. He knew he would be asked a number of questions at arrival about his occupation, his health status, his living arrangements, etc., and he was prepared. As he approached the immigration officer, the first American he had ever met, the answers tumbled out in a nervous jumble, “Work factory! No coff-coff! Tooths very good! Go to Chicago! Buy house! Big house!”

The officer shook his head, laughed, and asked, “Name?”

Thinking the officer was mocking his presumptuous housing plan, he replied, “OK. OK … rent.” And that’s how we became the Okrent family.

This story is not true. Most stories of this kind are not true. Because, as Philip Sutton of the New York Public Library explains, the inspectors at Ellis Island “did not create records of immigration; rather they checked the names of the people moving through Ellis Island against those recorded in the ship’s passenger list, or manifest.” No names were changed at Ellis Island, because no names were taken at Ellis Island.

It is also highly unlikely that such comically inept communication would have ever taken place at Ellis Island. According to this article at U.S. Citizenship and Immigration Services, the Ellis Island immigrant inspectors all “spoke an average of three languages. They were assigned to inspect immigrant groups based on the languages they spoke. If the inspector could not communicate, Ellis Island employed a full-time army of interpreters and would call in temporary interpreters under contract to translate for immigrants speaking the most obscure tongues.”

So how did Jensen become Johnson, Koenigsberger become Kingsley, Mlodzianowski become Murphy, and so on? In some cases, names were entered incorrectly on the passenger list when travelers bought their tickets abroad. For example, a Portuguese named Teixeira, leaving from a French port, might have been entered as Techera. These types of mistakes were in fact sometimes corrected by Ellis Island inspectors (by lightly marking corrections, at the request of the passenger, above the name written in the manifest).

In other cases, immigrants were given alternate names by neighbors, bosses, co-workers, or teachers who couldn’t pronounce the originals. Those alternate names were then adopted by the immigrants when they submitted their applications for naturalization. Though the idea for the new name might have come from someone else, the name did not become official unless the immigrant chose to make it official when becoming a citizen.

The name you used when you applied for your naturalization papers did not have to match the manifest at Ellis Island. Names were adjusted, sometimes slightly, in order to fit new surroundings, and sometimes drastically, in order to fit new identities. My name, which was Okręt in the old country, was changed to Okrent to get as close as possible to the intended pronunciation (the ę is a nasalized e in Polish). Official name changes did not come about through haphazard errors, but because immigrants deliberately chose them. Chalk it up to the urge to assimilate, the drive for self-reinvention, or the excitement of using a freedom they hadn’t had before, but don’t blame it on the hardworking, multilingual clerks at Ellis Island.

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Stephen Missal
crime
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New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
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A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]

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